Repeatability of a Highly Stable Permanent Seismic Source Evaluated Through Long-Term Operation at the Aquistore CO2 Injection Site
Bibliographic record
Abstract
Abstract Time-lapse seismic is often used for reservoir monitoring. Although some case studies have been reported, especially for offshore oil fields, similar onshore Abu Dhabi studies have been limited. Onshore monitoring challenges are mainly due to hard carbonate reservoir rock, in which fluid displacement invokes only minor changes in rock properties. Moreover, complex near-surface structures create strong surface-related noises such as surface waves and elastic scattering. These noises significantly degrade the repeatability if repeat data are recorded with positioning error of 1 meter. To address the problems above, permanent reservoir monitoring has been spotlighted recently. Although permanent receivers are widely used for seismology, few studies of permanent seismic sources have been reported. In this study, we demonstrate a permanent source, Accurately Controlled Rotational Operated Signal System (ACROSS), which has a fixed position and excites highly repeatable seismic waves by rotating an accurately controlled eccentric mass. We deployed ACROSS at the Aquistore CCS test field onshore in Canada and recorded the wavefield with permanent receivers buried underground. The ACROSS system was operated several times throughout one year. The data acquired in a continuous 45 day operation were analyzed to calculate variation of amplitudes. The result indicated that we had obtained very stable waveforms with less than 3% variation if the data is stacked sufficiently. We also compared the two datasets acquired at different times of the year by calculating the normalized root mean square (NRMS) as a repeatability index. The histogram showed that the peak of NRMS distribution approached ~15% with only front and back mute processing. These results support our conclusion that an ACROSS system has potential to be used for reservoir monitoring in onshore fields by providing highly repeatable data for an extended time period.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".